We are looking for a platform engineer to build the infrastructure that powers our next-generation machine learning research. Think: large-scale experimentation, distributed training, and reproducibility.

This is not an applied ML role. You will not be fine-tuning LLMs or building agents. Instead, you will build the systems that enable researchers to train models at scale

• Distributed training pipelines for GPU-accelerated workloads (PyTorch, JAX)
• Experiment management and model versioning
• Resource scheduling on on-premise HPC clusters and cloud (Slurm, Kubernetes)
• Observability and debugging for complex training jobs
• Data lineage and artifact tracking

• 2+ years building large-scale distributed systems for research or data-intensive...